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Design, Modeling, and Optimization of Power Electronics SystemsVirtual Prototyping
Andrija Stupar, Andreas Müsing
Hilton Hotel, Nürnberg, 27.10.2011.
• State of “Virtual Prototyping” today: Problems
• Solution: PE Design Suite with GeckoCIRCUITS as the core
• Comparison via design example:
- Analytical approach to converter design and optimization
- Simulation approach and its advantages
• Modeling Different Design Domains: Electrical, Magnetic, Thermal: Modeling Everything as a Circuit?
• Coupling Domains: Model Reduction and Simplification
Outline
Motivation
• Power Electronics Engineer must consider many factors when making design decisions:
- System performance & Efficiency
- Power Density (Volume, size) & Weight
- Cost, Reliability, etc.
• Must deal with Thermal & Electromagnetic issues
• Many choices to make:
- Topology?
- Control/modulation scheme?
- Components?
Need Virtual Prototyping: evaluate on a computer, relatively quickly, a large number of design possibilities, and gain insight into relationships between the different aspects of the design problem.
State of “Virtual Prototyping” Today
• Generally speaking, the theory to do virtual prototyping already exists
• It seems that we have software tools for almost all necessary domains:
- Very detailed and precise circuit simulators (e.g. SPICE, etc.)- Very powerful electromagnetic simulators (e.g. Maxwell)- 3D-FEM simulators for thermal design (e.g. Icepak, COMSOL)
• We have a large body of knowledge on the behaviour of power electronics (PE) and the necessary sub-components
• So what is the problem?• Tedious: it takes very long to set up all relevant models• Tools not made specifically for PE: large skill set needed• Detailed simulation slow; not easy to transfer relevant data• Result: Engineer concludes not worth the effort, does limited
simulation and calculations, relies on past designs, experience and actual prototyping
• Solution: Create a software package that has relevant models and simulators, is fast, and “fits well” with the knowledge of PE engineers
Optimization Example: Analytical Approach
Optimization goal: Maximum Efficiency (99%)
Phase-shift PWM DC-DC Converter for Telecom Power Supplies (5 kW)Papers: Badstuebner, Biela, and Kolar, APEC 2010 and IPEC 2010
Derive steady-stateOperating point
- Formulae for RMS, average currents, voltages
- FFT for AC losses(check by simulation)
Set up loss models
Optimization procedure
Java program/Maple script
Built prototype:
Calc. eff.: 98.9%Meas. eff: 98.5%
Optimal design
Optimization Example: Analytical Approach
• How long does this take, start to finish? (not incl. prototype construction)
- Derive and setup all models: 2-4 months
- Execute optimization procedure: 1-2 weeks
• Great deal of effort required
• Want to try different topology?
• Change operating mode?
• Change control/modulation scheme?
• Error in deriving analytical models?
• Change of components, geometries?
• The need for a better, more general approach is clear
Start again, from beginning
Start again
Start again
Start again
New loss models needed
Optimization by Simulation: Requirements
• Replace as much as possible analytical work by numerical simulation:
Build model in PE-engineer-friendly software environment
Do minimum amount of simulation necessary
Extract automatically from simulation results all required parameters for system evaluation
Coupling of Physical Domains
Is this a realistic approach for a PE Design?
Multi-Domain Simulation in Power Electronics
Thermal Solver (FDM)
CircuitSimulator
• PE Engineer challenged with different domains
• Circuit Simulator should be „central part“ of design toolbox
• Direct tool interconnection not realistic
Consider different abstraction levels (model order reduction)
Circuit interpretationpossible?
• Power Circuit
• Electromagnetics
• Thermal
• Magnetics
HF Magnetics(Losses)
EM Solver (Parasitics, EMI)
Cooling System (Heatsink)
PE Circuit Simulator: GeckoCIRCUITS
• Model of converter for simulation
Circuit model
Control modelPI control
Java block simulates any control/modulation scheme
Calculate loss of semiconductors Thermal RC circuit model
of semiconductor + heat sink
Send temperature waveforms to scope
Setting Model Parameters in GeckoCIRCUITS• For virtual prototyping and optimization, must be able to simulate, change
system parameters, simulate again, change parameters, simulate…
Shouldn’t do this manually every time
GeckoSCRIPT: model manipulation and simulation control scripting environment within GeckoCIRCUITS
Functions to set all model parameters, control simulation, simulate step-by-step, or by time interval
Full Java API available, can utilise full power of Java programming language
Tutorial for GeckoSCRIPT available on GeckoCIRCUITS CD
Extract relevant information from simulation
• Need: RMS, avg, min/max values of currents, voltages, FFT of signals…Available via scope
Automate via GeckoSCRIPT
RMS, etc. values
Fourier series coefficients
GeckoCIRCUITS: Steady-State Detection
• Usually interested what happens during steady-state operation
• GeckoSCRIPT provides functions for periodic steady-state operation: simulate until steady-state and stop, then extract parameters
Stops when steady-state reached
All analytical analysis of power converter circuit has been replaced by simulation!
Currently (v.1.5) works for PWM DC-DC systems- Development ongoing to cover other types of systems
Loss Modeling: Semiconductors
• Rather than simulate semiconductors in great detail to extract all losses from parasitics, etc. (too slow), have functionally correct model for PE circuits for fast simulation
• Use electrical simulation results to calculate losses based on loss models - > data entered from data sheet curves or experimental measurements
Transfer characteristic (conduction losses)
Turn-on and turn-off energies(switching losses)
“Real-time” loss and temperature curves produced by simulation
Loss Modeling: Passives
• Current GeckoCIRCUITS version (1.5): still must work-out and enter loss models for inductors, transformers, capacitors “by hand” (standard models available in literature for most common arrangements)
Enter loss model formulae for passive components here:
Code optimization loop here
“Plug-in” extracted data (RMS, avg., FFT)
Comparison: Analytic vs. Simulation
• Optimum system, switching frequency 16 kHz
Efficiency:- Analytical calculations: 98.9%- Derived from simulation: 98.8%
Comparison: Analytic vs. Simulation
• Possible converter design, switching frequency 50 kHz
Efficiency:- Analytical calculations: 98.7%- Derived from simulation: 98.6%
Comparison: Analytic vs. Simulation
Analytical Simulation
Calculate one operating point: ~1 s Calculate one operating point: 8 s (slower)- to be much improved in the future!
Set-up model: month(s) Set-up model: days – 2 weeks (much faster)
Model adaptability: low to none, difficult Model adaptability: high and simple
Results: match well
Non-linearities: difficult (e.g. Coss) Non-linearities: easy
• Variable / adaptive simulation step-width √
• Fast direct steady state calculation √
• Reluctance models for transformers / magnetic circuits √
• Magnetics losses calculation √
• More detailed switch models (MOSFETS, bipolar transistors, …)
• Built-in optimization algorithms
• Connection of GeckoCIRCUITS to 3D field solvers:- GeckoEMC: calculation of layout parasitics √- GeckoHEAT: 3D finite element thermal simulation √
Future Development of GeckoCIRCUITS (Version 2.0)
Further increasescalculation speed Optimization!
Version 2.0 Release: June 2012
Thermal Modeling & Simulation: GeckoHEAT
• Easy-to-use, very fast
• Various boundary-conditions - Power loss density- Convection boundary- Fixed temperature
• Automatic extraction ofthermal impedance network
• Standard approach to thermal simulation: 3D-FEM simulation when necessary: slow and cumbersome
• GeckoHEAT: Finite-difference method (FDM) based approach to thermal modeling and simulation: thermal RC (impedance) circuits
• Computation time reduction compared to 3D-FEM: hours minutes, minutes seconds
• Conduction problems only: convection too complex
Inductor Modeling: Reluctance model
Electric Network Magnetic Network
Conductivity
Resistance
Voltage
Current / Flux
/R l A
m /R l A2
1
dP
P
V E s 2
1
m dP
P
V H s
dA
I J A
dA
B A
E-Core Reluctance model
Inductor Loss Modeling
• Winding losses: analytic formulae well known and reasonably accurate
• Problem: Core losses: Improved generalized Steinmetz eqn.:
- DC bias not considered!
- Relaxation effect not considered
- Steinmetz parameters are valid only in a limited flux density and frequency range
v0
1 d dd
T
iBP k B t
T t
Core Loss Modeling including DC Bias• Further improved generalized Steinmetz Equation:
n
lll
T
i PQtBtBk
TP
1rr
0v d
dd1
• Must measure core losses to parameterize the equation!• Need database of core material measurements in simulation tool
Loss measurements “Loss map” database
Simulated flux waveform
r r r, , , , , , ,ik k q Equation parameters
Accurate core loss calculation
• Experimentally verifiedpapers: J. Muehlethaler, J. W. Kolar, et al., ICPE 2011, APEC 2011, IPEC 2010
Simulated by reluctance model
GeckoMAGNETICS: 3D Tool for Inductor Loss CalculationsCurrently in DevelopmentInputs:
• Core Dimensions
• Winding properties (roundconductor, Litz Wire, FoilConductors & arragement)
• Material Database (B-H curve,Steinmetz paramters, loss map)
• Current/Flux waveforms (e.g. from GeckoCIRCUITS, FFT)
• Inductor thermal model
Output:
• Total losses & loss distribution
• Inductances
• Field distribution
Electromagnetic Modeling: GeckoEMC• 3D electromagnetic modeling and simulation
- Parasitics in modules, components
- Layout parasitics
- EMI filters
• Can be done with 3D FEM/FDM usually very slow
• Solution: Partial Element Equivalent Circuit Method (PEEC)
Model EM properties as a circuit, utilize fast circuit solver
Electromagnetic Modeling: GeckoEMC• Module modeling:
Maxwell 3D: 1 h 20 min
GeckoEMC: 30 sec
• EMI Filter modeling:- Coupling effects considering geometric arrangement
PFC input filter stage Measurements match simulation
papers: I. Kovacevic, A. Muesing, J. W. Kolar, et al., CEFC 2010, IPEC 2010, COMPUMAG 2011
Currently works only with toroidal inductors
Coupling GeckoCIRCUITS and GeckoEMC
• EMI analyzed in GeckoCIRCUITS(Test Receiver block)
Thermal Solver (FDM)
CircuitSimulator
HF Magnetics(Losses)
EM Solver (Parasitics, EMI)
Cooling System (Heatsink)
• Waveform can be fed into GeckoEMC
Combining Simulation Domains – MOR
Motivation: Finally, we want to include thermal models and electromagnetic models (parasitics) into a circuit simulation
• Typical: Thermal or EM solver contains > 10000 cells
• Circuit simulation: dt = 100 nsec, T = 1 sec
This is impossible to solve together
• Our future solution approach: Model Order Reduction (MORe)
MORe: Construct a simplified system to approximate the original system with reasonable accuracy.
Thermal Solver (FDM)
CircuitSimulator
HF Magnetics(Losses)
EM Solver (Parasitics, EMI)
Cooling System (Heatsink)
Gecko-Research Software Overview
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